The co-chaperone p23 promotes prostate cancer motility and metastasis.

Prostate cancer is an androgen receptor (AR)-dependent malignancy at initiation and progression, therefore hormone therapy is the primary line of systemic treatment. Despite initial disease regression, tumours inevitably recur and progress to an advanced castration-resistant state a major feature of which is metastasis to the bone. Up-regulation of AR cofactors and chaperones that overcome low hormone conditions to maintain basal AR activity has been postulated as a mechanism of therapy relapse. p23, an essential component of the apo-AR complex, acts also after ligand binding to increase AR transcriptional activity and target gene expression, partly by increasing chromatin-loaded holo-receptor-complexes. Immunohistochemical studies have demonstrated increased p23 expression in advanced prostate cancer. Here, we further characterise p23 roles in AR signalling and show that it modulates cytosolic AR levels in the absence of hormone, confirming a chaperoning function in the aporeceptor complex and suggesting p23 upregulates AR signalling at multiple stages. Moreover, p23 protein levels significantly increased upon treatment with not only androgen but also clinically relevant anti-androgens. This was in contrast to the HSP90 inhibitor 17-AAG, which did not modulate expression of the cochaperone - important given the HSP90-independent roles we and others have previously described for p23. Further, we demonstrate p23 is implicated in prostate cancer cell motility and in acquisition of invasiveness capacity through the expression of specific genes known to participate in cancer progression. This may drive metastatic processes in vivo since analysis of prostate tumour biopsies revealed that high nuclear p23 significantly correlated with shorter survival times and with development of metastases in patients with lower grade tumours. We propose that increased p23 expression may allow cells to acquire a more aggressive phenotype, contributing to disease progression, and that p23 is a plausible secondary target in combination with HSP90 inhibition as a potential therapy for advanced prostate cancer.

A methodological approach to unravel organ-specific breast cancer metastasis.

Breast cancer is the most commonly diagnosed and the second highest cause of cancer-related mortality. Although major breakthroughs have emerged during the past decades concerning the characterization of major malignant tumors hallmarks, little is known about the molecular process that sustains the most deadly feature of cancer: metastasis to distant organs. In fact, this colonization of tumor cells to secondary sites is not random but rather orientated, and depends on several signalling events that are not fully elucidated yet. Understanding the precise molecular and cellular mechanisms accountable for the specific invasion of tissues by breast cancer cells is likely to be important for developing new therapeutic strategies to effectively prevent metastasis in patients diagnosed with early cancer lesions. Here, we briefly describe a multidisciplinary approach based on the molecular profiling of breast cancer metastases, the elaboration of prognostic gene signatures, the clinical validation and the experimental confirmation using cell and animal models to better address breast cancer metastasis. This methodology can be considered as a useful workflow to identify and validate the genes that trigger and support organ tropism of breast cancer cells during metastasis.

Role of the focal adhesion protein kindlin-1 in breast cancer growth and lung metastasis.

BACKGROUND: Fermitin family member 1 (FERMT1, Kindlin-1) is an epithelial-specific regulator of integrin functions and is associated with Kindler syndrome, a genetic disorder characterized by skin blistering, atrophy, and photosensitivity. However, the possible role of kindlin-1 in cancer remains unknown. METHODS: Kindlin-1 expression was quantified in several human cancers using quantitative real-time polymerase chain reaction and published microarray datasets. The association between kindlin-1 expression and patient metastasis-free survival (N = 516) was assessed with Kaplan-Meier analyses. Effects of ectopic expression or silencing of kindlin-1 on cell signaling, migration, and invasion were assessed in human breast cancer cell lines using western blotting, immunofluorescence, wound healing assays, and invasion on Matrigel or type I collagen substrates. Breast tumor growth and lung metastasis were evaluated in 12-week-old female BALB/c mice (10 controls and six Kindlin-1-knockdown mice). All statistical tests were two-sided. RESULTS: Kindlin-1 expression was consistently higher in tumors than in normal tissues in various cancer types metastasizing to the lungs, including colon and bladder cancer. Kindlin-1 expression was associated with metastasis-free survival in both breast and lung adenocarcinoma (breast cancer: hazard ratio of lung metastasis = 2.55, 95% confidence intervals [CI] = 1.39 to 4.69, P = .001; lung cancer: hazard ratio of metastasis = 1.96, 95% CI = 1.25 to 3.07, P = .001). Overexpression of kindlin-1 induced changes indicating epithelial-mesenchymal transition and transforming growth factor beta (TGFß) signaling, constitutive activation of cell motility, and invasion (number of migrating cells, Kindlin-1 cells vs control, mean = 164.66 vs. 19.00, difference = 145.6, 95% CI = 79.1 to 212.2, P = .004; invasion rate, Kindlin-1-cells vs control = 9.65% vs. 1.92%, difference = 7.73%, 95% CI = 4.75 to 10.70, P < .001). Finally, Kindlin-1 depletion in an orthotopic mouse model statistically significantly inhibited breast tumor growth (P < .001) and lung metastasis (P = .003). CONCLUSION: These results suggest a role for kindlin-1 in breast cancer lung metastasis and lung tumorigenesis and advance our understanding of kindlin-1 as a regulator of TGFß signaling, offering new avenues for therapeutic intervention against cancer progression.

Confounding effects in "a six-gene signature predicting breast cancer lung metastasis": reply.

Molecular signatures have begun to elucidate the biological and molecular mechanisms underlying the phenotypic diversity of breast tumors. Breast tumors are characterized by five different molecular subtypes that are associated with distinct clinical outcomes in terms of prognosis, treatment response, and site of relapse. In particular, the basal-like and luminal B subtypes of tumors are more aggressive and have a higher tendency to metastasize to the lung than do the other subtypes. Given this difference in metastatic profiles of breast tumors, the six-gene signature (6GS) that we showed to be predictive of lung relapse was reexamined in the context of the tumor subtypes. This first analysis suggested that the 6GS is a surrogate for molecular subtype, discriminating basal-like tumors rather than tumors that metastasize to the lung. Here, we show that the 6GS discriminates the two overlapping features, the basal-like subtype and the tendency to metastasize to the lung. Nevertheless, the 6GS predicts lung metastases of breast tumors independent of the molecular subtypes.

A six-gene signature predicting breast cancer lung metastasis.

The lungs are a frequent target of metastatic breast cancer cells, but the underlying molecular mechanisms are unclear. All existing data were obtained either using statistical association between gene expression measurements found in primary tumors and clinical outcome, or using experimentally derived signatures from mouse tumor models. Here, we describe a distinct approach that consists of using tissue surgically resected from lung metastatic lesions and comparing their gene expression profiles with those from nonpulmonary sites, all coming from breast cancer patients. We show that the gene expression profiles of organ-specific metastatic lesions can be used to predict lung metastasis in breast cancer. We identified a set of 21 lung metastasis-associated genes. Using a cohort of 72 lymph node-negative breast cancer patients, we developed a 6-gene prognostic classifier that discriminated breast primary cancers with a significantly higher risk of lung metastasis. We then validated the predictive ability of the 6-gene signature in 3 independent cohorts of breast cancers consisting of a total of 721 patients. Finally, we show that the signature improves risk stratification independently of known standard clinical variables and a previously established lung metastasis signature based on an experimental breast cancer metastasis model.

Gene arrays for diagnosis, prognosis and treatment of breast cancer metastasis.

The advent of microarray tools has generated a massive amount of gene expression data. These data have greatly enhanced our understanding of the biology of breast cancer metastasis and provide a way to improve the prediction of the metastatic potential of breast tumours. Gene-expression profiling has highlighted the molecular heterogeneity of mammary tumours and contributed to the identification of a new molecular classification of breast cancers. In addition, several molecular signatures predicting the likelihood of distant metastases for breast cancer patients have been characterized. Further reports have described gene expression profiles associated with specific metastatic phenotypes, including the organ preference of breast cancer metastasis. Here we review the major studies that had important impacts on the understanding of breast cancer metastasis. We also discuss the future challenges in this research field and the special issues that still need to be examined.